The present invention relates generally to processing online interaction and more particularly to process different modes of online interactions.
Corporations are increasingly interacting with their customers online. More and more people are going online to get information, buy products and obtain support. The number of Internet users surpassed 400 million in 2000 and will continue to grow to reach 1.17 billion by 2005. In addition, wireless devices, such as cell phones and personal digital assistants, are significantly penetrating into the corporate operations. By 2005, more people will be accessing the Internet wirelessly than through the landlines. Corporations are bombarded by online interactions from many different fronts. Information embedded in these interactions is extremely valuable. They guide corporations to understand their customers and chart their own future.
Most people go to corporate sites for specific purposes, and corporations have to respond appropriately. One approach is through call centers. On average, it costs a company about $33 to respond to a single call. Not only is it expensive to operate call centers, the employee mobility of such centers is high. Typically, these employees do not stay for more than six months. They are the front line soldiers interfacing directly with customers. With such a high mobility rate, it is challenging to maintain a solid group of well-trained staff.
A number of companies try to reduce cost with automatic response or self-help systems. Such systems are much cheaper than systems based on direct contacts with customer support personnel. They typically cost in the order of less than $1 a call. Also, they function 24 hours a day and 7 days a week, and they can respond to at least a portion of the interactions.
However, typical automatic systems only focus on one type of interactions, such as self-help or email. Corporations should have a unified view of customer interactions. If a customer asks a question through email, he should get the same response as from self-help through his browser.
There are companies trying to provide systems to give the same answers for different types of interactions. Their approach is to transform different types of interactions into a specific format. For example, through an email and through a chat session, a user asks a question, “Where are you located?” Their system transforms both interactions into the same format. Then they respond to that same format. Presumably, such a system can help them resolve the challenge of inconsistent responses from different systems. As in other instantaneously responding systems, if they can accurately respond to 30% of incoming inquiries, they are already a money saver and may be considered a success.
In recent years, a field known as customer relationship management (CRM) has flourished. The goal of a CRM system is to allow companies to track customers, monitor revenue and expenses and target marketing prospects more accurately. The CRM market has grown from $500 million in 1996 to $6 billion in 2001. To save money, many companies are using self-help as a part of their CRM systems to respond to their customers instantaneously. Such automatic response systems are becoming more pervasive in the industry.
Systems that focus on providing instantaneous responses to customers are emphasizing on the 24/7 auto-response aspects of the systems. However, such systems have weaknesses.
Focusing on providing instantaneous responses addresses a real need in the industry. But such quick results are not always accurate or appropriate. Also, since quick response is the goal, such systems do not handle information previously collected from different systems. Unfortunately, 90% or more of corporate information is the latter type. They were previously collected, at different time frames and in many different formats/protocol. They can be located in diverse geographical locations. To really understand customers, corporations should consolidate and analyze current and past information together.
Not only can aggregating such information help corporations better understand their customers, they can help corporations improve on their response systems. For example, a corporation has a CRM system with self-help dialog boxes, email support and kiosks. A customer is interested to buy a personal computer, but does not know what type. He can go to the corporate Web site, identify himself and ask for personal computers from the corporation's search dialog box. Assume the search dialog box on the site responds with a bad answer. A day later, the customer emails a similar inquiry to the corporation, and gets an email response. Then, an hour later, the customer goes to the corporation's kiosk and orders the computer. It would be very advantageous if the CRM systems can analyze all of the above interactions together from the three touch points—the search dialog box, the email system and the kiosk. Based on the analysis, the system can conclude that (a) the email response enhances the final sale; and (b) the search dialog box's response was defective in responding to questions on personal computers.
Online interactions are coming into corporations in different protocols, and from different time frames and physical systems. Some of the interactions can be stored in a database. Other interactions can be in writing and stored in word documents. Interactions can be occurring now, or might have occurred two weeks ago. To understand customers, corporations need to consolidate as many interactions as possible current and past, local and remote—and analyze them appropriately. From the understanding, corporations would be able to better serve their customers, determine what products to make and, in turn, chart their future. Corporations have to be able to intelligently and accurately extract such knowledge from the avalanche of online interactions. It should be apparent from the foregoing that this is a big challenge.